Using precisely methods from network science we can design powerful models and simulation tools for what-if analysis of different urban planning scenarios [1]}, [2]}. Singapore, due to the complexity of its transport system, is precisely a global city where such tools would be particularly valuable [3]}.
Network science applied to the study of transport systems has proved to be increasingly useful in recent years. Xu and González [4]} have shown that a slight re-routing of a fraction of daily car commutes produces significant reductions in traffic, thus alleviating the congestion state of the overall transport system. In this perspective the development of data-driven analytic tools can help control the transport system and improve both the customer's travel experience and the system's overall efficiency. Çolak et al. [5]} have investigated the interplay of number of vehicles and road capacity to determine the level of congestion in urban areas. In particular, they show that the ratio of the road supply to the travel demand can explain the percentage of time lost in congestion. De Domenico et al. [6]} show that the efficiency in exploring the transport layers depends on the layers' topology and the interconnection strengths.
